ASSIGN: Context-Specific Genomic Profiling of Multiple Heterogeneous Biological Pathways

Authors

Ying Shen, Boston University
Moom Roosan, Chapman UniversityFollow
Stephen R. Piccolo, Boston University
Daniel Gusenleitner, Boston University
Nader N. El-Chaar, University of Utah
Luis Cheng, University of Utah
Stefano Monti, Boston University
Andrea H. Bild, University of Utah
W. Evan Johnson, Boston University

Document Type

Article

Publication Date

1-22-2015

Abstract

Motivation: Although gene-expression signature-based biomarkers are often developed for clinical diagnosis, many promising signatures fail to replicate during validation. One major challenge is that biological samples used to generate and validate the signature are often from heterogeneous biological contexts—controlled or in vitro samples may be used to generate the signature, but patient samples may be used for validation. In addition, systematic technical biases from multiple genome-profiling platforms often mask true biological variation. Addressing such challenges will enable us to better elucidate disease mechanisms and provide improved guidance for personalized therapeutics.

Results: Here, we present a pathway profiling toolkit, Adaptive Signature Selection and InteGratioN (ASSIGN), which enables robust and context-specific pathway analyses by efficiently capturing pathway activity in heterogeneous sets of samples and across profiling technologies. The ASSIGN framework is based on a flexible Bayesian factor analysis approach that allows for simultaneous profiling of multiple correlated pathways and for the adaptation of pathway signatures into specific disease. We demonstrate the robustness and versatility of ASSIGN in estimating pathway activity in simulated data, cell lines perturbed pathways and in primary tissues samples including The Cancer Genome Atlas breast carcinoma samples and liver samples exposed to genotoxic carcinogens.

Availability and implementation: Software for our approach is available for download at: http://www.bioconductor.org/packages/release/bioc/html/ASSIGN.html and https://github.com/wevanjohnson/ASSIGN.

Comments

This article was originally published in Bioinformatics, volume 31, issue 11, in 2015. https://doi.org/10.1093/bioinformatics/btv031

Dr. Moom Roosan was known as Mumtahena Rahman at the time of publication.

Recommended Citation

Shen Y, Rahman M, Piccolo SR, et al. ASSIGN: Context-specific genomic profiling of multiple heterogeneous biological pathways. Bioinformatics. 2015;31(11):1745-1753. https://doi.org/10.1093/bioinformatics/btv031

Copyright

The authors